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GongRzhe

Quickchart-MCP-Server

by GongRzhe
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JavaScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: 'download_chart' focuses on saving a chart image to a file, while 'generate_chart' focuses on creating the chart itself. There is no overlap or ambiguity between these operations.

    Naming Consistency5/5

    Both tool names follow a consistent verb_noun pattern ('download_chart' and 'generate_chart'), using snake_case and clear action verbs. This makes them predictable and easy to understand.

    Tool Count2/5

    With only two tools, the server feels under-scoped for a chart generation domain. It lacks essential operations like updating, deleting, or listing charts, which limits its utility and completeness.

    Completeness2/5

    The tool set is severely incomplete for chart generation. It covers creation and downloading but misses critical operations such as updating chart data, deleting charts, or retrieving existing charts, leaving significant gaps in the workflow.

  • Average 2.8/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

  • This repository is archived. Archived repositories automatically receive an F maintenance tier.

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

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Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior2/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'Generate a chart' but fails to explain key traits such as output format (e.g., image URL, binary data), authentication needs, rate limits, or error handling. This is a significant gap for a tool with complex inputs and no output schema.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is extremely concise with a single sentence, 'Generate a chart using QuickChart', which is front-loaded and wastes no words. It efficiently states the core action without unnecessary elaboration.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the complexity (5 parameters, nested objects, no output schema, and low schema coverage), the description is incomplete. It lacks details on output, error cases, and parameter usage, making it inadequate for an AI agent to effectively invoke this tool without guesswork.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters2/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is low at 40%, with only 'type' and 'labels' having descriptions. The tool description does not compensate by explaining parameters like 'datasets', 'title', or 'options', leaving most parameters undocumented. This adds minimal value beyond the sparse schema information.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose3/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description states the tool 'Generate a chart using QuickChart', which provides a clear verb ('Generate') and resource ('chart'), but it's vague about the specific action—it doesn't specify what type of chart generation (e.g., creating an image, URL, or embed) or distinguish it from the sibling tool 'download_chart'. This leaves ambiguity in the exact purpose beyond basic chart creation.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    There is no guidance on when to use this tool versus alternatives like 'download_chart' or other charting methods. The description lacks context about prerequisites, scenarios for use, or exclusions, leaving the agent without direction on appropriate application.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations provided, the description carries full burden for behavioral disclosure. While 'Download' implies file system write operations, it doesn't specify permissions needed, whether existing files are overwritten, what image formats are supported, or error conditions. The description mentions default save locations but lacks other critical behavioral details for a file-writing tool.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single, efficient sentence that communicates the core functionality without unnecessary words. It's appropriately sized for a simple tool and front-loads the essential information. Every word earns its place.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a tool that writes files to the local system with no annotations and no output schema, the description is insufficient. It doesn't address important contextual aspects like supported image formats, error handling, file naming conventions, or what happens when the outputPath directory doesn't exist. The agent lacks critical information for reliable tool invocation.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    With 100% schema description coverage, the baseline is 3. The description doesn't add meaningful parameter semantics beyond what's in the schema - it mentions the outputPath default behavior which is already documented in the schema description. No additional context about the 'config' object structure or validation is provided.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the action ('Download') and resource ('a chart image to a local file'), making the purpose immediately understandable. However, it doesn't distinguish this tool from its sibling 'generate_chart' - while 'download' implies saving to a file versus 'generate' which might create in memory, this distinction isn't explicitly stated in the description.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides no guidance on when to use this tool versus its sibling 'generate_chart'. There's no mention of prerequisites, alternative approaches, or specific scenarios where this tool is preferred. The agent must infer usage from the tool name alone.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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